howellx/qwen25-7b-scientific-reasoning

TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Feb 27, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

howellx/qwen25-7b-scientific-reasoning is a 7.6 billion parameter Qwen2.5-Instruct model fine-tuned by howellx for enhanced scientific and mathematical reasoning. It specializes in providing explicit, step-by-step chain-of-thought explanations for complex problems, including mathematical word problems and logic puzzles. This model is optimized for educational contexts and applications requiring transparent problem-solving processes.

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Qwen2.5-7B Scientific Reasoning: Enhanced Problem Solving

This model, developed by howellx, is a fine-tuned version of the Qwen2.5-7B-Instruct base model, specifically optimized for scientific and mathematical reasoning tasks. It leverages 525 chain-of-thought examples to generate explicit, step-by-step solutions, making its thought process transparent.

Key Capabilities

  • Explicit Reasoning: Provides detailed "Let me think through this:" prefixes to show its problem-solving approach.
  • Step-by-Step Solutions: Breaks down complex problems into manageable, easy-to-follow steps.
  • Self-Verification: Often includes self-checking mechanisms to ensure accuracy.
  • Pedagogical Value: Designed to be highly educational, ideal for teaching and learning problem-solving strategies.
  • Targeted Optimization: Excels in mathematical word problems, scientific reasoning, and logic puzzles.

Training Details

The model was fine-tuned using LoRA (Low-Rank Adaptation) with a rank of 16 and alpha of 32, targeting key attention and feed-forward modules. Training involved 3 epochs over 189 steps, resulting in a significant reduction in training loss from 1.19 to 0.47. While maintaining the accuracy of the base model, it offers more verbose and pedagogically valuable responses.

Good for

  • Educational tutoring and homework assistance.
  • Teaching and demonstrating problem-solving methodologies.
  • Applications requiring transparent, verifiable reasoning.
  • Scientific and mathematical problem-solving contexts.